Unlike the supervised case, we adopt a different method to satisfy the information separation requirement. When \(s^i\)  and \(h^i\)  are independent in probability, the mutual information between them comes to zero, i.e., no shared information between \(s^i\)  and \(h^i\) .
Here we apply an alternative definition of mutual information, Total Correlation (TC) penalty [1]}, [2]}, which is a popular measure of dependence for multiple random variables.
